Author
Listed:
- Muhammad Begawan Bestari
- Muhammad Palar Wijaya
- Dolvy Girawan
- Nenny Agustanti
- Eka Surya Nugraha
Abstract
Background: Developing a non-invasive model is essential for assessing liver stiffness in conditions without transient elastography, which will determine further management in chronic hepatitis B (CHB) patients. Objectives: This study aims to evaluate the interleukin-13 role in liver fibrosis and develop a new predictive model that includes interleukin-13 and standard data such as age and platelet count. Methods: Patients were recruited from Hasan Sadikin General Hospital’s CHB registry from October 2021 to January 2022. Patients underwent demographic data collection, complete blood count, interleukin-13, and transient elastography examinations on the same day. The platelet count variable was listed in ×109/ dL, and the interleukin-13 in pg/mL. Interleukin-13 values were categorized as positive for IL-13 with a cut-off of 5 pg/mL (ILcut5). The liver stiffness measurement was inverted to obtain a normal distribution and became inverseLSM as the model’s outcome. The prediction model was formed through multiple linear regression analysis. Results and Discussion: The number of patients studied was 88. A prediction model for inverseLSM was formulated, had an R2 of 0.37, and consisted of age, platelet count, and ILcut5 with correlation coefficients of -0.221, 0.326, and −0.288, respectively. The model had no autocorrelation, multicollinearity, or significant outliers, a normal distribution appearance, and met the homoscedastic criterion. Elevated IL-13, decreased platelet count, and aging are linked to increased liver stiffness.
Suggested Citation
Muhammad Begawan Bestari & Muhammad Palar Wijaya & Dolvy Girawan & Nenny Agustanti & Eka Surya Nugraha, 2026.
"Unveiling the role of interleukin-13 in liver fibrosis of chronic hepatitis B patients: Development of a predictive model,"
PLOS ONE, Public Library of Science, vol. 21(3), pages 1-9, March.
Handle:
RePEc:plo:pone00:0344791
DOI: 10.1371/journal.pone.0344791
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